A key in navigation through virtual environments or designing autonomous vehicles (that can successfully navigate through and manipulate their environment) is the ability to effectively create, maintain, and use an accurate 3-D model of a desired world. A system which can rapidly, reliably, remotely and accurately perform measurements in three-dimensional space for the mapping of indoor environments is required for many applications.
The literature reports a spectrum of mobile mapping and navigation technologies and systems, the majority of which are either in a prototype stage or in a design/simulation stage. Among these systems, none is suitable for indoor mapping since they either do not meet the accuracy requirement or use sensors not suited for indoor applications.
Table 1 displays the properties of four mapping and three navigation systems. Mobile mapping systems combine absolute and relative positioning devices and imaging sensors to locate features in a global reference system. The absolute positioning sensors provide the framework for all other data collected by the relative positioning sensors. Global positioning systems (GPS) are used in all mobile mapping systems which claim high absolute accuracy. Other positioning sensors such as inertial navigation systems (INS) and/or dead-reckoning devices are also required for positioning and orientation to fill in the gaps when a GPS signal is interrupted or temporarily obstructed. When the data from these sensors are properly integrated, a continuous and accurate tracking of the absolute vehicle position becomes possible.
TABLE 1 __________________________________________________________________________ Typical mobile mapping and navigation systems Organization System Name Sensors Application __________________________________________________________________________ Ohio State U., USA GPSVan GPS, INS, wheel counter, Road Mapping CCD& color video cameras U. Armed Forces, KiSS GPS, INS, Odometer, Road Mapping Germany Altimeter, CCD& color video cameras. Tech. School Aachen, Surveying GPS, Wheel sensors, Road Mapping Germany Vehicle Barometer, stereo CCDs Geofit Inc., Canada VISAT GPS, INS, CCD & Road Mapping color video cameras. CMU, USA Ambler Laser radar scanner, dead Local mapping reckoning devices. for locomotion CMU, USA Navlab Stereo CCDs, laser radar Navigation scanner, Doppler, sonar. Lockheed-Martin & 10 UGV-RSTA Color, infrared stereo video Navigation other companies and cameras, laser radar, GPS, /recognition research labs. tilt meters, flux-compass (Military) __________________________________________________________________________
In order to determine the position of the features and details to be mapped, imaging sensors such as charge-coupled devices (CCD cameras) are used. These cameras will determine the feature position relative to the vehicle. Since the vehicle's absolute position in a global coordinate system is known from the absolute positioning sensors, any mapped feature relative to the vehicle can easily be transferred to this global system. The final accuracy is a function of the accuracy of each of the individual sensors, the calibration and registration of the sensor positions relative to each other, and the rigorous processing and integration of data. Currently the best achievable accuracy reported from existing systems, using state-of-the-art GPS/INS/digital CCD cameras, is 1-3 m (RMS) in the global framework and 0.5 m for relative position between features.
From table 1, it is obvious that the mapping systems which claim high accuracy are all designed for road mapping and not useful for indoor application since they all rely on GPS for positioning. They also use stereo vision alone to obtain the relative position of features, thus only an incomplete 3-D map can be constructed. Although the navigation systems do not use GPS and incorporate laser scanners for complete 3-D mapping, they do not construct a complete map and do not require absolute accuracy. The main application areas of these systems are highway or road mapping, structural clearance measurements along railways, and aerial topographic mapping. Since most of the existing prototypes for mobile mapping systems do not use laser scanners (those are used only in navigation systems) many surface details are not detected (using only passive CCD cameras).
For mapping applications, GPS provides accurate location information. In some locations, GPS signals may not be available and estimation of absolute location is made. Once a GPS signal is again acquired, absolute distance is established, thereby correcting any error which was introduced by the estimation. For use indoors, GPS is not available as it requires signal reception of satellite transmissions. Over a small distance, estimation of absolute location allows for relatively good modeling results. Unfortunately, errors propagate from each estimate to all subsequent estimates because each estimate of location is at best based on a previous estimate. In modeling a mine or a building, the cumulative errors result in unacceptable inaccuracies.
In many of the above noted systems, measurements are made relative to a mobile platform while a precise absolute position is not determined due to inaccuracy (error accumulation) of dead-reckoning devices (wheel odometers) or inertial navigation systems. Further, absolute locations are not determined because they are unnecessary. In navigation, a question to be answered is how a device is to move from where it is. It need not establish where it is. Thus, cumulative error in mapping is insignificant, and error correction solely for navigational purposes occurs as necessary. For navigation, differential comparisons between frames is performed to establish differences from where a device was to where it is now.